In March, the Data Quality Campaign (DQC) convened federal and state data leaders to discuss key challenges with and opportunities for modernizing statewide longitudinal data systems (SLDSs). During the day-long gathering, Reimagining State Data Systems: A Federal–State Conversation, participants unpacked state and federal strategies to transform SLDSs so that they enable the kinds of access to data that people need to navigate smooth education and workforce pathways—as outlined in DQC’s vision for data access. We’ve collected key themes that emerged during the robust conversation, alongside actionable strategies and recommendations to address each theme at both the state and federal level.
Addressing Information Gaps in State Data Systems
States often face hurdles in supporting individuals’ transitions between education and the workforce due to incomplete data and gaps in data sharing, which particularly affect those eligible for public assistance. Participants’ recommendations for addressing these gaps include:
- Leverage the influence of governors. Governors can play a pivotal role in closing information gaps by using their bully pulpit to advocate for high-quality, integrated data across state systems. Their leadership can foster cross-agency collaboration, ensuring systems that deal with financial aid, public benefits such as the Supplemental Nutrition Assistance Program (SNAP), and unemployment insurance (UI) wage data are connected and support individuals’ needs more effectively.
- Update federal guidance. Federal agencies such as the Department of Labor (DOL), and the US Department of Agriculture’s (USDA) Food and Nutrition Service (FNS) should update their guidance on the sharing and use of key data such as UI wage data and SNAP eligibility data to provide greater clarity on when and how states can share this data. Clarity could facilitate the integration of state and federal data in a way that enhances support for individuals who are eligible for both state and federal benefits.
Modernizing State Data Systems and Ways of Doing Business Simultaneously
The complexity and diversity of state data systems, when coupled with out-of-date operational approaches, significantly impedes information exchange and cross-agency collaboration. Participants’ recommendations for modernizing processes that can support reimagined SLDSs include:
- Promote the adoption of automation. By using artificial intelligence (AI), privacy enhancing technologies, and other forms of automation for repetitive tasks, state leaders can increase efficiency and improve data service delivery to individuals.
- Ensure sustainable funding. The two key sources of federal funding for SLDSs, the SLDS and Workforce Data Quality Initiative (WDQI) grant programs, should be funded at higher levels and should be revised to provide increased flexibility to states. This action from federal leaders would enable state leaders to innovate to make data work better for individuals, the public, and policymakers alike.
Addressing Data Privacy Barriers
Efforts to integrate data across various sectors are often hampered by individual officials’ interpretations of federal and state privacy laws. To address these privacy challenges, participants recommended that leaders:
- Consult outside experts. Seeking third-party legal counsel can help state data leaders navigate the complex landscape of data privacy laws. Neutral, expert advice can help clarify what is permissible under state and federal privacy laws, facilitating more confident data sharing and interoperability.
- Clarify federal privacy guidance. Updated and unambiguous federal guidance from the US Department of Education (ED) and DOL on the privacy implications of sharing data, such as financial aid and UI wage data, could remove significant barriers to data access.
Building and Sustaining Human Capacity
Recruitment and retention of data professionals and SLDS personnel can be hindered by competitive markets and bureaucratic hiring practices. Participants’ recommendations for increasing human capacity include:
- Explore partnership opportunities. State data leaders should consider partnering with local universities to create co-op, training, and apprenticeship opportunities that increase the hiring pool and improve candidate skill sets in their state.
- Allow SLDS funds to be used for investing in capacity. Federal leaders should expand the SLDS grant program to allow its funds to be used not just for technology upgrades, but also increased human capacity. These funds could support hiring, enhancing the skills and capacity of data system staff, and restructuring career ladders and trajectories for data professionals.
Enhancing Federal Funding Frameworks for State Data Systems
A lack of clarity and flexibility in federal funding structures impedes the effective maintenance and modernization of SLDSs. Participants’ recommendations to improve federal funding structures include:
- Provide explicit guidance on using grant funds to support integrated data. Federal agencies need to update their grant guidance to incorporate the Office of Management and Budget’s (OMB) new guidance on using federal grant dollars to support data system integration, data sharing, data analysis, and human capacity. Doing so would clarify that many existing federal dollars can be used to enable cross-agency (and cross-state) data sharing, access, and use.
- Integrate data-driven outcomes into grant applications. Embedding reporting requirements for data-driven outcomes into federal grant applications, specifically SLDS and WDQI grants, would incentivize leaders to create and maintain robust, effective SLDSs.
Fostering Research Partnerships and Technical Assistance
Bureaucratic hurdles and the slow pace of cross-state processes often create barriers to effective research and technical assistance partnerships. Participants’ recommendations for making it easier to create such partnerships include:
- Promote public forums for research priorities. State leaders should actively identify and communicate their research agendas in public forums. This can attract research partners and highlight opportunities for collaboration that lead to actionable insights and policy improvements.
- Develop a shared repository of tools and guides. To streamline technical assistance, federal leaders should create an open source “tool shed” where state leaders can both contribute to and draw from a pool of resources like code bases, contract templates, and privacy guides. State leaders might still need to seek expert assistance on some issues, but this “tool shed” would enable states to easily resolve commonplace issues by themselves.
State and federal leaders’ willingness to engage in a robust dialogue about challenges, potential solutions, and paths forward toward meaningful data access demonstrates participants’ commitment to working collaboratively to reimagine the data ecosystem in a way that centers people’s education and workforce data needs. Although the road ahead will have its challenges, this collective resolve bolsters DQC’s confidence that momentum is building toward a day when people will have access to the data they need to make informed choices about their education and career journeys.
DQC is committed to offering our continued support to state and federal leaders—guided by our recent vision for what meaningful data access looks like, and our state recommendations and federal recommendations to support data access. We’re ready to provide resources and expertise as we advocate to ensure that data works for everyone navigating their education and workforce journeys.
